Research
Print page Print page
Switch language
The Capital Region of Denmark - a part of Copenhagen University Hospital
Published

Calibration of bioelectrical impedance analysis for body composition assessment in Ethiopian infants using air-displacement plethysmography

Research output: Contribution to journalJournal articleResearchpeer-review

DOI

  1. Bone turnover, calcium homeostasis, and vitamin D status in Danish vegans

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. The efficacy of a high protein/low glycemic index diet intervention in non-obese patients with asthma

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Fat catch-up Growth in early infancy and cardiometabolic outcomes at 5 years of age

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

  2. Global epidemiology of use of and disparities in caesarean sections

    Research output: Contribution to journalComment/debateResearchpeer-review

  3. Body mass index Growth in early life and cardiometabolic markers and body composition at 5 years of age - a latent class trajectory analysis

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

  4. Does health literacy predict trajectories of cardiometabolic markers in people with diabetes?

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

  5. Associations between birth weight and glucose intolerance in adulthood among Greenlandic Inuit

    Research output: Contribution to journalJournal articleResearchpeer-review

View graph of relations

BACKGROUND/OBJECTIVES: Assessment of infant body composition (BC) is crucial to understand the consequences of suboptimal nutritional status and postnatal growth, and the effects of public health interventions. Bioelectrical impedance analysis (BIA) is a feasible, relatively inexpensive and noninvasive method for assessing BC. However, very little research has been conducted in low- and middle-income populations, where efforts to prevent or treat malnutrition in early life are a public health priority. We aimed to develop equations for predicting fat-free mass (FFM) and fat mass (FM) based on BIA in 0- to 6-month-old Ethiopian infants.

SUBJECTS/METHODS: The study comprised a total of 186 BC assessments performed in 101 healthy infants, delivered at Jimma University Specialized Hospital. Infant air-displacement plethysmography (IADP) was the criterion method, whereas weight, length, sex, age and an impedance index (L(2)/Z50) were predictors. Prediction equations were developed using stepwise multiple linear regression and the accuracy was evaluated with a 10-fold cross-validation approach.

RESULTS: A linear regression model based on body weight, age and sex predicted FFM, estimated by IADP, with an adjusted R(2) and root mean square error (RMSE) of 0.94 and 200 g, respectively. Adding impedance index to the model resulted in a significantly improved model fit (R(2)=0.95; RMSE=181 g). For infants below 3 months of age, inclusion of impedance index did not contribute to an improved model fit for predicting FFM compared with a model already comprising weight, sex and age.

CONCLUSIONS: The derived equations predicted FFM with acceptable accuracy and may be used in future field surveys, epidemiological studies and clinical trials conducted in similar sub-Saharan African population groups aged 0-6 months.

Original languageEnglish
JournalEuropean Journal of Clinical Nutrition
Volume69
Issue number10
Pages (from-to)1099-104
Number of pages6
ISSN0954-3007
DOIs
Publication statusPublished - Oct 2015

    Research areas

  • Adipose Tissue, Age Factors, Anthropometry, Body Composition, Body Fluid Compartments, Body Weight, Calibration, Electric Impedance, Ethiopia, Female, Humans, Infant, Infant, Newborn, Linear Models, Male, Mathematical Concepts, Models, Biological, Nutritional Status, Plethysmography, Sex Factors, Journal Article, Research Support, Non-U.S. Gov't, Validation Studies

ID: 51755284